spambayes

In the three or four years I’ve been fighting unwanted e-mail messages with better tools than the Delete key I’ve tried almost a dozen different tools. This is a quick (ha!) survey of the ones I’ve used, and why I don’t (or do) still use them.

My very first anti-spam tool was something called Mailfilter. I used it for my personal e-mail on Mac OS X, wrote about it here, and almost immediately afterwards lost a non-spam message to an aggressive keyword match. That was the end of Mailfilter. I can’t even remotely recommend it, as it’s just not intelligent enough (strict, single expression matching), and had zero safety net.

My next attempt at a solution was a utility called SpamFire. Like Mailfilter, it is a “pre-filter,” which means it would run before my e-mail client, download my mail, and skim out the spam. Unlike Mailfilter, it actually saved the trapped messages, so if it made a mistake, I could recover the message. It had plenty of other differences from Mailfilter, which I wrote about previously, and which made it so useful that it became the first anti-spam tool I paid for. But in the end I switched to a different tool because SpamFire was separate from my e-mail client, and that made it cumbersome to use.

A while back I recommended an Outlook plug-in called SpamNet, from Cloudmark. At the time, it was a free tool for Outlook users to block spam, that worked quite reliably. Sadly, it’s no longer free. I get so little spam at work (where my e-mail address is relatively unpublished) that I can’t justify buying a subscription.

Like SpamNet, it can be installed as an Outlook plug-in, and easily used via buttons on Outlook’s toolbar. But the technology behind it is very different, as it uses Bayesian filtering rather than distributed recognition. It’s also different in that the core project and recognition engine is command line-oriented; the Outlook-only plug-in is terrific, but only a side project. It’s not required, and there are plenty of ways for those who use something other than Outlook for e-mail to use SpamBayes.

You can read the review for a thorough look, but my experience was that it was just as easy to install as SpamNet, is extremely effective at blocking spam, and is also having fewer false positives. I think the reason for that is SpamNet uses other people’s spam reports to decide what to block in my Inbox, and there’s a lot of people who just block e-mails they signed up for (newsletters, promos, etc.), rather than unsubscribe from them. Those false reports pollute the knowledge base, and affect my results. Bayesian filtering is exactly the opposite — it only cares what I think is spam.

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